Added the file

HelpingMentalAsst.py

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+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+
+# Load the HelpingAI2.5-10B model
+model_name = "HelpingAI/HelpingAI2.5-10B-1M"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Helper function to generate response
+def generate_response(user_input):
+    chat = [
+        {"role": "system", "content": "You are HelpingAI, an emotional AI specialized in medical assistance. Understand the user's mental state through their text and respond empathetically."},
+        {"role": "user", "content": user_input}
+    ]
+
+    inputs = tokenizer.apply_chat_template(
+        chat,
+        add_generation_prompt=True,
+        return_tensors="pt"
+    ).to(model.device)
+
+    outputs = model.generate(
+        inputs,
+        max_new_tokens=256,
+        do_sample=True,
+        temperature=0.6,
+        top_p=0.9,
+    )
+
+    response = outputs[0][inputs.shape[-1]:]
+    return tokenizer.decode(response, skip_special_tokens=True)
+
+# Define Gradio app
+def chatbot(user_input):
+    try:
+        response = generate_response(user_input)
+        return response
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+
+# Gradio interface
+description = """
+### HelpingAI - Medical Assistance Chatbot
+
+This AI is designed to provide empathetic medical assistance. It understands the user's mental state through text and provides relevant responses.
+"""
+
+demo = gr.Interface(
+    fn=chatbot,
+    inputs=gr.Textbox(label="Enter your message", placeholder="Describe your medical concern or feelings..."),
+    outputs=gr.Textbox(label="HelpingAI Response"),
+    title="HelpingAI Medical Assistance",
+    description=description,
+    theme="compact",
+)
+
+if __name__ == "__main__":
+    demo.launch()